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Can I run Qwen3-VL 30B-A3B (MoE) locally?

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Ollama weight files: Q4_K_M 20 GB (qwen3-vl:30b); Q8_0 34 GB (qwen3-vl:30b-a3b-instruct-q8_0).

Yes on 47 machines in this list. The smallest is RTX 3060 12GB: Q4_K_M, about 20.3 GB, roughly 21 tokens per second, via LM Studio. lms get unsloth/Qwen3-VL-30B-A3B-Instruct-GGUF@Q4_K_M

Setup on DGX Spark 128GB (NVIDIA, ASUS, Dell, Lenovo, HP, MSI, Acer, Gigabyte)

Open Qwen3-VL 30B-A3B (MoE) in the checker

Hardware that fits

HardwareRuntimeQuantMemoryFitSpeedCommand
RTX 3060 12GBLM StudioQ4_K_M GGUF20.3 GBpartial offload (slower)~21 tok/slms get unsloth/Qwen3-VL-30B-A3B-Instruct-GGUF@Q4_K_M
RTX 4070 12GBLM StudioQ4_K_M GGUF20.3 GBpartial offload (slower)~22 tok/slms get unsloth/Qwen3-VL-30B-A3B-Instruct-GGUF@Q4_K_M
RTX 5070 12GBLM StudioQ4_K_M GGUF20.3 GBpartial offload (slower)~23 tok/slms get unsloth/Qwen3-VL-30B-A3B-Instruct-GGUF@Q4_K_M
RTX 4060 Ti 16GBOllamaQ4_K_M21.7 GBpartial offload (slower)~23 tok/sollama run qwen3-vl:30b
RTX 4070 Ti Super 16GBOllamaQ4_K_M21.7 GBpartial offload (slower)~29 tok/sollama run qwen3-vl:30b
RTX 4080 16GBOllamaQ4_K_M21.7 GBpartial offload (slower)~29 tok/sollama run qwen3-vl:30b
RTX 5080 16GBOllamaQ4_K_M21.7 GBpartial offload (slower)~31 tok/sollama run qwen3-vl:30b
RX 7800 XT 16GBOllamaQ4_K_M21.7 GBpartial offload (slower)~29 tok/sollama run qwen3-vl:30b
RX 9070 XT 16GBOllamaQ4_K_M21.7 GBpartial offload (slower)~29 tok/sollama run qwen3-vl:30b
RTX 3090 24GBOllamaQ4_K_M21.7 GBfits in fast memory~146 tok/sollama run qwen3-vl:30b
RTX 4090 24GBOllamaQ4_K_M21.7 GBfits in fast memory~157 tok/sollama run qwen3-vl:30b
RX 7900 XTX 24GBOllamaQ4_K_M21.7 GBfits in fast memory~149 tok/sollama run qwen3-vl:30b
M1 Pro 32GBOllamaQ4_K_M21.7 GBfits in fast memory~41 tok/sollama run qwen3-vl:30b
M2 Pro 32GBOllamaQ4_K_M21.7 GBfits in fast memory~41 tok/sollama run qwen3-vl:30b
M4 32GBOllamaQ4_K_M21.7 GBfits in fast memory~25 tok/sollama run qwen3-vl:30b
M3 Pro 36GBOllamaQ4_K_M21.7 GBfits in fast memory~31 tok/sollama run qwen3-vl:30b
Mac Studio M4 Max (32c GPU) 36GBOllamaQ4_K_M21.7 GBfits in fast memory~85 tok/sollama run qwen3-vl:30b
Mac Studio M5 Max (32c GPU) 36GBOllamaQ4_K_M21.7 GBfits in fast memory~95 tok/sollama run qwen3-vl:30b
RTX 5090 32GBOllamaQ4_K_M21.7 GBfits in fast memory~279 tok/sollama run qwen3-vl:30b
M4 Pro 48GBOllamaQ8_035.7 GBfits in fast memory~33 tok/sollama run qwen3-vl:30b-a3b-instruct-q8_0
Mac Studio M4 Max (40c GPU) 48GBOllamaQ8_035.7 GBfits in fast memory~67 tok/sollama run qwen3-vl:30b-a3b-instruct-q8_0
Mac Studio M5 Max (40c GPU) 48GBOllamaQ8_035.7 GBfits in fast memory~75 tok/sollama run qwen3-vl:30b-a3b-instruct-q8_0
M1 Max 64GBOllamaQ8_035.7 GBfits in fast memory~49 tok/sollama run qwen3-vl:30b-a3b-instruct-q8_0
M2 Max 64GBOllamaQ8_035.7 GBfits in fast memory~49 tok/sollama run qwen3-vl:30b-a3b-instruct-q8_0
M3 Max 64GBOllamaQ8_035.7 GBfits in fast memory~49 tok/sollama run qwen3-vl:30b-a3b-instruct-q8_0
M4 Max 64GBOllamaQ8_035.7 GBfits in fast memory~67 tok/sollama run qwen3-vl:30b-a3b-instruct-q8_0
Mac Studio M4 Max (40c GPU) 64GBOllamaQ8_035.7 GBfits in fast memory~67 tok/sollama run qwen3-vl:30b-a3b-instruct-q8_0
Mac Studio M5 Max (40c GPU) 64GBOllamaQ8_035.7 GBfits in fast memory~75 tok/sollama run qwen3-vl:30b-a3b-instruct-q8_0
DGX Spark 64GB (ASUS, Dell, HP, MSI, Acer, Gigabyte)OllamaQ8_035.7 GBfits in fast memory~48 tok/sollama run qwen3-vl:30b-a3b-instruct-q8_0
Mac Studio M3 Ultra 96GBOllamaQ8_035.7 GBfits in fast memory~100 tok/sollama run qwen3-vl:30b-a3b-instruct-q8_0
Mac Studio M5 Ultra 96GBOllamaQ8_035.7 GBfits in fast memory~146 tok/sollama run qwen3-vl:30b-a3b-instruct-q8_0
M3 Max 128GBOllamaQ8_035.7 GBfits in fast memory~49 tok/sollama run qwen3-vl:30b-a3b-instruct-q8_0
M4 Max 128GBOllamaQ8_035.7 GBfits in fast memory~67 tok/sollama run qwen3-vl:30b-a3b-instruct-q8_0
Mac Studio M4 Max (40c GPU) 128GBOllamaQ8_035.7 GBfits in fast memory~67 tok/sollama run qwen3-vl:30b-a3b-instruct-q8_0
Mac Studio M5 Max (40c GPU) 128GBOllamaQ8_035.7 GBfits in fast memory~75 tok/sollama run qwen3-vl:30b-a3b-instruct-q8_0
DGX Spark 128GB (NVIDIA, ASUS, Dell, Lenovo, HP, MSI, Acer, Gigabyte)OllamaQ8_035.7 GBfits in fast memory~48 tok/sollama run qwen3-vl:30b-a3b-instruct-q8_0
M2 Ultra 192GBOllamaQ8_035.7 GBfits in fast memory~98 tok/sollama run qwen3-vl:30b-a3b-instruct-q8_0
2x Mac Studio M5 Max (40c GPU) 128GBllama.cppQ8_0 GGUF34.2 GBfits in fast memory~67 tok/sllama-server -hf unsloth/Qwen3-VL-30B-A3B-Instruct-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node
Mac Studio M3 Ultra 256GBOllamaQ8_035.7 GBfits in fast memory~100 tok/sollama run qwen3-vl:30b-a3b-instruct-q8_0
Mac Studio M5 Ultra (64c GPU) 256GBOllamaQ8_035.7 GBfits in fast memory~146 tok/sollama run qwen3-vl:30b-a3b-instruct-q8_0
Mac Studio M5 Ultra (80c GPU) 256GBOllamaQ8_035.7 GBfits in fast memory~146 tok/sollama run qwen3-vl:30b-a3b-instruct-q8_0
2x DGX Spark 128GBllama.cppQ8_0 GGUF34.2 GBfits in fast memory~43 tok/sllama-server -hf unsloth/Qwen3-VL-30B-A3B-Instruct-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node
4x Mac Studio M5 Max (40c GPU) 128GBllama.cppQ8_0 GGUF34.2 GBfits in fast memory~59 tok/sllama-server -hf unsloth/Qwen3-VL-30B-A3B-Instruct-GGUF:Q8_0 --rpc node2:50052,node3:50052,node4:50052 -c 8192 # run rpc-server on each other node
2x Mac Studio M5 Ultra (80c GPU) 256GBllama.cppQ8_0 GGUF34.2 GBfits in fast memory~130 tok/sllama-server -hf unsloth/Qwen3-VL-30B-A3B-Instruct-GGUF:Q8_0 --rpc node2:50052 -c 8192 # run rpc-server on each other node
Mac Studio M3 Ultra (80c GPU) 512GBOllamaQ8_035.7 GBfits in fast memory~100 tok/sollama run qwen3-vl:30b-a3b-instruct-q8_0
4x DGX Spark 128GBllama.cppQ8_0 GGUF34.2 GBfits in fast memory~38 tok/sllama-server -hf unsloth/Qwen3-VL-30B-A3B-Instruct-GGUF:Q8_0 --rpc node2:50052,node3:50052,node4:50052 -c 8192 # run rpc-server on each other node
4x Mac Studio M5 Ultra (80c GPU) 256GBllama.cppQ8_0 GGUF34.2 GBfits in fast memory~115 tok/sllama-server -hf unsloth/Qwen3-VL-30B-A3B-Instruct-GGUF:Q8_0 --rpc node2:50052,node3:50052,node4:50052 -c 8192 # run rpc-server on each other node

Estimates, not benchmarks. Model sizes are ollama.com download sizes; memory needed adds headroom for ~8k tokens of context; speeds are rough figures from memory bandwidth. Data updated 2026-10-18.

A project by OnDevice Labs · llms.txt